Sensorless Position Control of Permanent-Magnet Motors With Pulsating Current Injection and Compensation of Motor End Effects

Abstract

The sensorless position control of permanent-magnet motors is successfully implemented by superimposing a highfrequency voltage signal on the voltage reference or adding a high-frequency current signal to the current reference. The former approach is usually preferred because of its simplicity, although the latter one may allow better performance. This paper presents a new algorithm for the sensorless control of low-saliency permanent-magnet synchronous motors based on high-frequency sinusoidal current signal injection into the d-axis. Different from the related literature, the position information is derived by analyzing the measured high-frequency currents. The amplitude of the d-axis voltage reference is also exploited to improve performance. A proportional-integral (PI) controller plus a resonant term (PI-RES) is adopted to ensure the accurate tracking of both the dc and high-frequency components of the d-axis current reference. The main advantages of the proposed approach are the increased accuracy and sensitivity with respect to the approach based on voltage injection, the insensitiveness to inverter nonlinearities that are compensated by the current regulation loop, the actual control on the injected current value, and the practical absence of acoustic noise. Experiments on a linear tubular permanent-magnet synchronous motor prototype have been carried out to verify the aforementioned advantages. This paper also presents a discussion of the parameters of the PI-RES.

A Novel Method for Sensorless Speed Detection of Brushed DC Motors

“…The frequency of the ripple component is in a multiple of n/60 according to Equation (2), thus, it coincides with a frequency produced by the method explained in this subsection according to Equation (8). The ripple frequency corresponds to the index l = (2p·k)/η and it is the main component related to the motor speed.…”

“…Consequently, the observers work correctly when operating conditions are similar to the specified conditions, but they do not work as well when the operating conditions differ from the specified conditions. A first solution for this is to dynamically estimate the parameters of the model [7][8][9], but this generates a complex model that is usually nonlinear. A second solution is to use a nonlinear model of the brushed dc motor [10][11][12], or a technique that indirectly models the motor, such as Neural Networks [13,14] and the Kalman filter [15,16].…”

Flatness based sensorless control of PMSM using test current signal injection and compensation for differential cross-coupling inductances at standstill and low speed range

“…Information on the machine and the utilized test signal can be found in Table I to the broken symmetry of the linear machine, the coupling between the three winding strands is not equal. This effect has two consequences on the machine parameters [16], [10]. First, cross-coupling inductances m dq in the rotor oriented dq-coordinate system occur even if the fundamental currents are zero.…”

Harmonic Analysis of the Effects of Inverter Nonlinearity on the Offline Inductance Identification of PMSMs Using High Frequency Signal Injection

“…In order to meet the emerging demand for modern general-purpose drive applications, more attention should be paid to the offline parameter identification of PMSMs at standstill using only a voltage-source-inverter (VSI) fed drive. The d-q axis inductances of a PMSM obtained from offline identification using high frequency (HF) voltage injection are needed for the proper tuning of closed-loop controllers and the model-based sensorless control scheme [5]- [7]. These critical parameters should be acquired before motor startup.…”